We Can Use Machine Learning to Predict Obstructive Sleep Apnea
Author:
Affiliation:
1. Department of MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphia, Pennsylvania
2. Center for Biomedical Image Computing and AnalyticsUniversity of PennsylvaniaPhiladelphia, Pennsylvania
Publisher
American Thoracic Society
Link
https://www.atsjournals.org/doi/pdf/10.1164/rccm.202403-0666ED
Reference16 articles.
1. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis
2. Obstructive Sleep Apnea: Update and Future
3. Giving weight to incretin-based pharmacotherapy for obesity-related sleep apnea: a revolution or a pipe dream?
4. Identification of craniofacial risk factors for obstructive sleep apnoea using three-dimensional MRI
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